Bokeh绘图未使用下拉菜单更新。如何使用下拉菜单更改图形中的y值？

Question

我是初学者。我想创建一个数字，显示世界各地不同能源类型的生产情况。我在数据中使用了来自我们世界的两个数据集，我想制作一个下拉菜单，让您可以更改能源来源。我已经画出了一种能源，我已经创建了下拉菜单，但它还不起作用

我如何包括一个下拉菜单，使行变为显示来自另一列的数据（保留悬停工具和彩色行）？

数据来源： https://ourworldindata.org/grapher/nuclear-energy-generation?stackMode=absolute&time=2017&region=World&； https://ourworldindata.org/grapher/fossil-fuel-production?country=~OWID_WRL

from bokeh.io import show, output_file
from bokeh.plotting import figure, ColumnDataSource, curdoc
from bokeh.palettes import Category20_20
from bokeh.layouts import row
from bokeh.models import HoverTool, Select
import pandas as pd

#import datasets
df = pd.read_csv('nuclear-energy-generation.csv')
df_fossil_production = pd.read_csv('fossil-fuel-production.csv')
df = df.rename(columns={"Electricity from nuclear (TWh)": "TWh"})

#Filter for few countries for simplicity (temporary)
df = df.loc[df['Entity'].isin(["Netherlands", 'France', 'Belgium', 'Germany', 'Spain'])]
df_fossil_production = df_fossil_production.loc[df_fossil_production['Entity'].isin(["Netherlands",'France', 'Belgium', 'Germany', 'Spain'])]

#merge dataframes and convert to datetime
df_merge = pd.merge(df, df_fossil_production, on=["Entity", "Code", "Year"], how = 'outer')
df_merge["Datetime"] = pd.to_datetime(df_merge.Year, format='%Y')

#create figure for line
p = figure(title="Power generation",
            plot_width=1000,
            plot_height=250,
            x_axis_type='datetime',
            x_axis_label="Year",
            y_axis_label="Power generation (TWh)")

#plot the lines for nuclear energy production
for (name, group), color in zip(df_merge.groupby('Entity'), Category20_20):
    source = ColumnDataSource(group)
    p.line(x='Datetime', y='TWh', source=source, legend_label=str(name), color=color)

#create definition for the dropdown box
def callback(attr, old, new):
    if new == 'Nuclear': 
        source.data = {
            'x' : df_merge["Year"],
            'y' : df_merge["TWh"]}
    else:
        source.data = {
            'x' : df_merge["Year"],
            'y' : df_merge["Coal Production - EJ"]}

#create dropdown menu
select = Select(title="Energy type", options=['Nuclear', 'Fossil'], value='Nuclear')
select.on_change('value', callback)
layout = row(select, p)
curdoc().add_root(layout)

# Create a HoverTool: hover
hover = HoverTool(tooltips=[('Country', '@Entity'),
                            ('Production (TWh)', '@TWh'),
                            ('Year', '@Year')], mode='vline') 

# Add the hover tool to the figure p
p.add_tools(hover)

output_file('line.html')
show(layout)